Политизированные сообщества в социальной сети «ВКонтакте»: фракции и их влияние

Many important nature evolution phenomena can be explained with Self-organized criticality (SOC) theory. SOC theory explains the tendency of large dissipative systems to drive themselves into a scale-invariant critical state without parameter adjustment. These phenomena are of crucial importance because fractal objects displaying SOC are found. This paper analyzes the characteristics of SOC theory, and then introduces basic principles of SOC theory in one-dimension model. Based on the self-organized criticality owned by the high-density pedestrian evacuation and even the trample event, this paper proposes the potential applications of SOC theory to explain the various phenomena in pedestrian evacuation from public buildings in unconventional emergencies.

Punctuated equilibrium is regarded as the state of natural and social systems manifested in occasional intense, quick bursts of activity. Within the framework of the theory of self-organized criticality (SOC), punctuated equilibrium can be formalized as pink noise. SOC theory, having been developed by the end of 1980s, was originally intended to explain natural science phenomena. However, soon after its presentation, it began to spread across the social and humanitarian field of knowledge. Critical state is one on the brink of a bifurcation point. It turns out that some systems can stay in a state of permanent choice for a fairly long time. The author presents the examples of punctuated equilibrium revealed in computer experiments with artificial societies, as well as through empirical observation (particularly, in the dynamics of voting patterns, internet activity, and protest movements in the past and present). The key concepts of SOC theory and tools for pink noise identification are laid out. The sandpile model has been given special attention. Certain papers have been analyzed in which SOC theory was applied to gain some political science knowledge. According to SOC, in certain cases, there is no need to search for some significant extraordinary factor to shed light on explosive social transformations (including revolutions and other bursts of social and political activity). Social transformations can be induced by quite ordinary - and thus undistinguished - properties of systems, micro-level pro- cesses, and local impulses. SOC theory, therefore, refocuses the attention of researchers from the search for direct causes of events to the identification of states of the subject that generates these events.

Using the R/ S statistic to analyze AE data

Emerged in the domain of natural science, the theory of self-organized criticality (SOC) has spread to various fields over the past decades, achieving the status of an interdisciplinary paradigm. This article aims to answer three questions: Is SOC really a ubiquitous property of social reality? Does the SOC theory really substantiate the fundamental unpredictability and inevitability of social catastrophes? What contribution can the SOC theory make to clarifying the fundamental mystery of the relationship between human will and historical necessity? I performed a meta-analysis of the latest literature and summarized the results of my own case studies. So far, there is not enough empirical data to confirm that SOC is ubiquitous, although it has been proven that SOC is characteristic of many social systems—especially those in a borderline, transitional state. The SOC theory supports the idea that in some social systems for a fairly long time (even by historical standards), human will, act, and opinion can have a fundamental impact on the development of the whole of a system.

This article reviews empirical and theoretical studies conducted over the past three decades that apply the approaches and tools of self-organized criticality (SOC) theory to research in the fields of history, political science, and sociology. The expansion of SOC into the social sciences and humanities reflects a demand for methodological frameworks capable of addressing research problems related to fundamental issues of complexity and instability. Originating in the natural sciences, SOC has evolved into a meta-disciplinary paradigm. Its integration into historical and socio-political research has given rise to a distinct line of inquiry that has not only demonstrated the applicability of the theory to the analysis of social systems but also revealed its considerable heuristic value. The expansion of SOC theory is an episode in a large and long-term interdisciplinary dialogue involving many ideas. This review analyzed the subject matter of this line of inquiry, highlighting the stages of its development from its initial emergence and outlining its key theoretical contributions. Special attention was paid to the design and heuristic potential of major studies. The reviewed literature typically identifies SOC patterns in empirical data—both historical and contemporary—and formulates hypotheses based on SOC models and universal explanatory frameworks. Where supported, these studies contribute to the advancement of domain-specific knowledge. SOC models play a heuristically significant role in this theory. They are the source of hypotheses and explanatory schemes, which are then tested for compliance with empirical data. At the center of the SOC theory is the “sand pile” model, which simulates all the key provisions of this concept. Several studies demonstrate that phenomena such as punctuated equilibrium and abrupt crises are characteristic of social systems exhibiting SOC behavior.

The air pollution in China currently is characterized by high fine particulate matter (PM2.5) and ozone (O3) concentrations. Compared with single high pollution events, such double high pollution (DHP) events (both PM2.5 and O3 are above the National Ambient Air Quality Standards (NAAQS)) pose a greater threat to public health and environment. In 2020, the outbreak of COVID-19 provided a special time window to further understand the cross-correlation between PM2.5 and O3. Based on this background, a novel detrended cross-correlation analysis (DCCA) based on maximum time series of variable time scales (VM-DCCA) method is established in this paper to compare the cross-correlation between high PM2.5 and O3 in Beijing-Tianjin-Heibei (BTH) and Pearl River Delta (PRD). At first, the results show that PM2.5 decreased while O3 increased in most cities due to the effect of COVID-19, and the increase in O3 is more significant in PRD than in BTH. Secondly, through DCCA, the results show that the PM2.5-O3 DCCA exponents α decrease by an average of 4.40% and 2.35% in BTH and PRD respectively during COVID-19 period compared with non-COVID-19 period. Further, through VM-DCCA, the results show that the PM2.5-O3 VM-DCCA exponents [Formula: see text] in PRD weaken rapidly with the increase of time scales, with decline range of about 23.53% and 22.90% during the non-COVID-19 period and COVID-19 period respectively at 28-h time scale. BTH is completely different. Without significant tendency, its [Formula: see text] is always higher than that in PRD at different time scales. Finally, we explain the above results with the self-organized criticality (SOC) theory. The impact of meteorological conditions and atmospheric oxidation capacity (AOC) variation during the COVID-19 period on SOC state are further discussed. The results show that the characteristics of cross-correlation between high PM2.5 and O3 are the manifestation of the SOC theory of atmospheric system. Relevant conclusions are important for the establishment of regionally targeted PM2.5-O3 DHP coordinated control strategies.

In emergency, the crowd evacuation from public buildings is the most important issue to save human lives. Panic generation and spread normally can lead to the unstable state -stampede during the crowd motion. The stability of crowd evacuation is a complex problem being researched for decades. This paper introduces self-organized criticality(SOC) theory to build the mapping model from a collective crowd into a sand pile with SOC. Therefore, the complex problem of stability analysis for crowd evacuation is converted into sandpiper stability analysis in a relatively simpler way.

Biological systems reach hierarchical complexity that has no counterpart outside the realm of biology. Undoubtedly, biological entities obey the fundamental physical laws. Can today's physics provide an explanatory framework for understanding the evolution of biological complexity? We argue that the physical foundation for understanding the origin and evolution of complexity can be gleaned at the interface between the theory of frustrated states resulting in pattern formation in glass-like media and the theory of self-organized criticality (SOC). On the one hand, SOC has been shown to emerge in spin-glass systems of high dimensionality. On the other hand, SOC is often viewed as the most appropriate physical description of evolutionary transitions in biology. We unify these two faces of SOC by showing that emergence of complex features in biological evolution typically, if not always, is triggered by frustration that is caused by competing interactions at different organizational levels. Such competing interactions lead to SOC, which represents the optimal conditions for the emergence of complexity. Competing interactions and frustrated states permeate biology at all organizational levels and are tightly linked to the ubiquitous competition for limiting resources. This perspective extends from the comparatively simple phenomena occurring in glasses to large-scale events of biological evolution, such as major evolutionary transitions. Frustration caused by competing interactions in multidimensional systems could be the general driving force behind the emergence of complexity, within and beyond the domain of biology.

The purpose of this study is to detect signs of political mobilization in social networks during the period of intensification of internal political struggle (including street actions of the opposition) at the beginning of 2021 in Russia. This study suggests a new quantitative indicator to reveal online communities (networks) characterized by strong user engagement and high level of political mobilization. VK-communities were mapped and analyzed in order to demonstrate the capability of this tool and determine levels of mobilization. The hypothesis of the study was that mobilized communities are able to turn virtual grievances into street protests. The object of study is a set (cluster) of related protest VK-communities (groups/hubs) through which messages from the most influential information donors are brought to public notice on the Internet. The proposed indicator for the calculation of mobilization level is based on the theory of self-organized criticality (SOC). The theory of SOC was initially created to describe a broad class of natural science phenomena, yet it has recently made its way into humanities and social sciences. Timeline of work: from January 10 to April 30, 2021. It was found that some groups (about 10%) in the considered cluster had a high mobilization index during this period. Many of the mobilized groups were very influential: they were both large-scale information donors and highly specialized protest communities. The practical significance of this study lies in improving the methods of monitoring network activity to identify groups that can influence the behavior of their members (both online and on the streets). This study also has theoretical significance related to the accumulation of knowledge about SOC effects in social systems.

Evidence for self-organized criticality in unscheduled downtime data of equipment

Archaeologists can learn from models of evolution as a self-organized critical phenomenon. Self-organized critical systems are large, interactive systems that organize into a critical state where minor events can trigger chain reactions. Such systems demonstrate power-law distributions in the size of changes, or “avalanches,” that occur. The theory of self-organized criticality is important in that it implies that the evolution of complex systems may be driven more by interactions between agents than by external events or natural selection. Stylistic changes may be examples of avalanches of interconnected events. Evidence for self-organized criticality is shown for stylistic evolution in historical pottery styles from New York State and is used to evaluate the nature of a prehistoric pottery typology from the Southwest.

The theory of self-organized criticality (SOC) is applicable for explaining powerful surges of protest activity on social media. The objects of study were two protest clusters. The first was a set of Facebook groups that promoted the impeachment of the Brazilian president Dilma Rousseff. The second was a set of groups on the social network Vkontakte that provided support for anti-government rallies in Armenia, referred to as Electric Yerevan. Numerous groups in the examined clusters were functioning in SOC mode during certain periods. Those clusters were able to generate information avalanches—seemingly spontaneous, powerful surges of creation, transmission, and reproduction of information. The facts are presented that supported the assumptions that SOC effects in social networks are associated with mass actions on the streets, including violence. The observations of SOC make it possible to reveal certain periods when the course of a sociopolitical system is least stable.

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We analyze long-term time series of daily average PM10 concentrations in Chengdu city. Detrended fluctuation analysis of the time series shows long range correlation at one-year temporal scale. Spectral analysis of the time series indicates 1/f noise behavior. The probability distribution functions of PM10 concentrations fluctuation have a scale-invariant structure. Why do the complex structures of PM10 concentrations evolution exhibit scale-invariant? We consider that these complex dynamical characteristics can be recognized as the footprint of self-organized criticality (SOC). Based on the theory of self-organized criticality, a simplified sandpile model for PM10 pollution with a nondimensional formalism is put forward. Our model can give a good prediction of scale-invariant in PM10 evolution. A qualitative explanation of the complex dynamics observed in PM10 evolution is suggested. The work supports the proposal that PM10 evolution acts as a SOC process on calm weather. New theory suggests one way to understand the origin of complex dynamical characteristics in PM10 pollution.

This issue is an enclosure to the theory of self-organized criticality (SOC) for studying of the radical protest groups of people in some social networks. The SOC theory needs for the value of level of the users involvement in Facebook communities which support the protest moves in Hong Kong in 2019. There were studied about 35 Facebook pages. The period of studying 01.03 to 23.03.2019. This article claims that the communities with the high level of users involvement are based on self-organized criticality. This item also explains some SOC theory approaches according to which a method of pink noise identity is one of the SOC attribute. It is necessary to say that some protest communities work in SOC regime. In spite of the seeming polycentric of the protest network the connection of reflection comes to a few number of Facebook pages which are the source of information and intension of the protesters so they can become the event’s drivers.